1. Field of the Invention
The present invention relates to a method and a system for the correction of an optical satellite image, and more specifically, to a method and a system for the correction of an optical satellite image which can correct satellite images in which pixel loss occurs.
2. Description of the Related Arts
Starting from No. 1 in 1972, Landsat, which is the first private remote sensing satellite for earth observation, was launched up to No. 7 in April, 1999, and only No. 5 and No. 7 have been currently operated.
As Landsat's satellite images accumulated for 40 years were distributed at no cost from the USGS of U.S.A., the satellite images have been globally widely used. However, the operation of a SLC (Scan Line Corrector) of Landsat 7 ETM+ (Enhanced Thematic Mapper Plus) stopped on May 31, 2003. Thus, as illustrated in (a) of FIG. 1, a defect that spectral information of about 25% of the images is not obtained was generated.
Thus, although Landsat 7 ETM+ enables earth observation to be easily performed with two times improved resolution than conventional sensors, the most users have used only images obtained before May 31, 2003.
To carry out continuous researches, NASA launched Landsat 8 on Feb. 11, 2013, but optical satellite images, which have been distributed at no cost from June 2003 up to date, are only Landsat 7 ETM+ images. Accordingly, researches for solving a SLC-off phenomenon has been steadily carried out all over the world.
However, restoration is complicated in processes and an enough interpolation method to carry out investigations has not been yet developed. Due to this, the images obtained after May 31, 2003 have been used in researches in a state of vacuums thereof being not restored. General users or companies also have much difficulty in utilizing the Landsat 7 ETM+ satellite images.
In the past, to solve the SLC-off phenomenon of Landsat 7 ETM+, a method of correcting omitted data areas by utilizing images obtained from the TM (Thematic Mapper) of Landsat 5 or SLC-on images captured around the same time, or other satellite images of similar spectrometric zones was used.
Such a method is advantageous that relative spectral information compared to performing interpolating within a single image can be obtained, but is disadvantageous that to restore one image, another image is required.
Also, when the irregular distribution of clouds or ground surface covering is changed, optical images are restored with wrong spectral information. Furthermore, since the optical images are greatly influenced by clouds, it would be very difficult to obtain an image not having the clouds at the time when the user desires.
As another conventional method, there is a method of filling in loss areas through interpolation using pixel values around loss areas within a single image.
Such a conventional interpolation method is advantageous that the interpolation could be performed within the single image. However, it is difficult to correct the loss areas, which reach a maximum of 13 pixels, using only the interpolation method. In a case where two-dimensional interpolation is performed, as illustrated in (b) of FIG. 1, a case in which the spreading of interpolated images occurs or spectral information having a large difference in peripheral pixel value is input is generated.
Due to this defect, the method of filling in the vacuums of the image to restore the image by utilizing the satellite image having the similar spectral zone and captured around the same time has been mainly used. Also, in Landsat images provided from the USGS, eight kinds of spectral information sources have been distributed in a GEOTIFF format, respectively. This interpolation process is problematic that it is very inconvenient and takes a long time to handle dozens or hundreds of data sources with commercial software.